Post on 31-Dec-2021
transcript
● The markets expected to almost double, from €1.7 t in 2016 to €3.2 t in 2025.
● Interoperability standard interfaces (both HW and SW), will be critical in reaping the benefits of Machine Learning/AI, particularly when
it comes to new GPU/CPU environments. These are the underpinnings of the cloud and IoT revolution, as they ensure speed, ease and
portability of data that is exchanged across distributed systems.
● Interoperability & value delivery, which will require seamless integration of different technologies – both hardware and software –
through semantic interoperability and heterogeneous integration.
European Coordinated Plan on Artificial Intelligence (AI)
• Ongoing partnerships between the Member States and the Union through joint undertakings such as ECSEL …. are key to processing big data and sustain further developments in AI.
• In 2019 and 2020, under the ECSEL Joint Undertaking, AI and data analytics will be integrated in lighthouse initiatives in manufacturing, mobility and personalized medicine, with a total budget of around EUR 200 million, from components up to full systems.
• Establishing world-reference testing facilities: An important step in bringing technology to market relates to experimenting and testing state-of-the art technology in real-world environments.
• Action is needed to facilitate sharing of data held by public and private sectors by creating a common European Data Space: a seamless digital area with the scale that will enable the development of new products and services based on data.
AI has a data quality problem
https://www.datainnovation.org/2019/03/ai-needs-better-data-not-just-more-data/
AI needs better data,
not just more data
Big data is so often improperly
formatted, lacking metadata, or
“dirty,” meaning incomplete,
incorrect, or inconsistent, that data
scientists typically spend 80
percent of their time on cleaning
and preparing data to make it
usable, leaving them with just 20
percent of their time to focus on
actually using data for analysis.
77% of professionals believe that interoperability is the largest challenge facing the industrial internet. © survey by IoT Nexus
ISO 10303 STEP Standards
development
1994: CAD
AP203
1999: PLM
AP214
2005: ILS
AP239
2014: CAE
AP242/209
CAD, Simulation, Manufacturing, Test, Sensor and Operational Data
in one standardized repository using ISO 10303. Facts or fiction?
Design CAD
Analysis FEM
Manufacturing
Sensor data
CAD, Simulation, Manufacturing, Test, Sensor and Operational Data
in one standardized repository using ISO 10303. Facts or fiction?
Design CAD
Analysis FEM
Manufacturing
Sensor data
• MBE will connect disciplines and modules
across entire enterprise
• Common understanding of different processes
and data disciplines
• Use terms and definitions to provide
interoperability for data exchange, sharing and
archival processes
ISO STEP 80%
STANDARDS
Conclusions: The challenges of the Information Age
● Interoperability of information technology, addressed by data exchange & sharing solutions
● Common enterprise-wide views of information, addressed by data integration solutions
● Obsolescence of information technology, addressed by data archiving solutions
● Freedom from vendor lock-in, addressed by open data solutions
● Multiple viewpoints, addressed by solutions embodying data independence